Finding data-driven answers based on real-world insights

Last month, the World Health Organization published a policy brief – “Ageism in artificial intelligence for health” – aimed at examining age-related bias in AI-based technology focused on the healthcare sector. AI has a tendency to replicate and exacerbate existing biases and disparities in care in earlier blog posts - something the WHO brief acknowledges, accepting that older people are at risk of being pushed aside as this new concept develops but also highlighting the myriad benefits to weaving AI and data analytics into the fabric of patient care. Fortunately, there are a number of relatively straightforward solutions that could address this issue, ensuring that that all demographics are catered to and able to benefit from the evolution of AI in healthcare.

Better understanding key demographics

One of the first key issues that springs to mind when it comes to older people specifically is the fact that this group might not have the best access or understanding of the technology and devices necessary for remote patient monitoring. In order to make this form of care sustainable in the long run, it’s essential that communities are equipped with the right tools to make this work – including access to education.

If telehealth services are going to become a realistic, long-term healthcare solution, the appropriate resources need to put in place to ensure equitable and fair access to treatment. Investment in digital infrastructure is essential to improving digital literacy not just for older individuals, but also for their caregivers and healthcare providers. We’re not just talking about walking people through the practical elements of telehealth: issues of consent and right to contest the use of AI are also a fundamental aspect of providing an aging population with the knowledge they need to choose for themselves.

Streamline existing structures through data-driven insights

Whilst AI is revolutionising many aspects of the healthcare sector, it’s still a relatively new field, and we’re continuously learning more about both its upsides and downsides. 

There’s so much potential for AI to change existing healthcare structures for the better – but only if everyone is included. By monitoring AI maturity, considering the nuances affecting particular demographics and altering approaches to telehealth accordingly, the healthcare sector has a golden opportunity to shake up approaches to treatment, resulting in a fairer and more equitable system.